Fig 1 - uploaded by Ebru Gökalp
Content may be subject to copyright.
Source publication
The application of new technologies in the manufacturing environment is ushering a new era referred to as the 4th industrial revolution, and this digital transformation appeals to companies due to various competitive advantages it provides. Accordingly, there is a fundamental need for assisting companies in the transition to Industry 4.0 technologi...
Citations
... After World War II, the world realized the power of technological advancements for propersecurity, fast communication and processing of information. It was addressed by embedding electronic systems such as relays, computers and PLCs in the industries and utilizing them for fast processing and communication to drive the operations of industry, that give birth to the Third Industrial Revolution termed as Industry 3.0 in the year 1969 [3].This revolution experienced thereplacement of manual activities in industry by automation systems, that improved the productivity of industries and gave rise to new subjects of intelligent such as mechatronics and robotics [4]. The concept of a new industrial revolution(Industry 4.0) wascoined by three engineers Hanning Kagermann, Wolfgang Wahlster and Wolf-Dieter Lukas [5]in the year 2011 at Hannover Trade Fair in Germany [5]. ...
Robotics & Automation book series aims at a key theme on Automation, Robotics and Applications. It is intended to provide a stimulating forum for researchers, scientists, engineers and practitioners to publish their latest research findings, ideas, developments and applications in all aspects of automation, robotics and sensors. The subjects include Adaptive Control Systems, Mobile and Autonomous Systems, Agriculture and Field Robotics, Robotics and Industrial Monitoring, Artificial Neural Networks in robotics or automation, etc, and their applications. More and more research will be centred on building robots and automation systems that can make a difference in the quality of human life. The days are not far when humanoid robots will be common in many homes and offices.
... The disruptive nature of the IR4.0 technologies has impacted several industrial processes; metrology is one of them, wherein data acquisition in real-time, big data handling, and inline process control, among others, are mostly demanding (Alonso et al., 2019). Since IR4.0 is characterised by the digitalisation and integration into the cyber-physical systems, the digitalization of metrological services leveraging the IR4.0 technologies is thus referred to as Metrology 4.0 (M4.0) (Cunha & Santos, 2020;Gökalp et al., 2017). De Groot and Schmidt (2021) stated that there is a deep discussion on whether metrology developments drive industry 4.0 or industry 4.0 drives metrology developments. ...
The digitalisation of metrological practices is paramount to ensure its full integration to enable various aspects, such as smart factories, online inspections, and real-time calibration, among others, in the manufacturing industry. The study explores various contributions of Industrial Revolution (IR4.0) technologies in digitalising metrological services, the interface between Metrology 4.0 (M4.0) and IR4.0, and M4.0 adoption factors. After the screening process, fifty-six scientific publications from Scopus, Open Science, ScienceDirect, and Google Scholar databases were involved in the study. It was found that the development of M4.0 and IR4.0 influence one another. For example, deploying inline metrology is critical to ensure real-time inspection, problem identification, and rectification to enable smart factories. Several critical factors were also identified to enable developing countries to adopt M4.0. The factors include the availability of a skilled workforce, infrastructure, management commitment, awareness of IR4.0 technologies, flexible organisation culture, investment capital, M4.0 standards, and norms for widespread adoption. Moreover, the study found several contributions of IR4.0 technologies in digitalising metrological practices in manufacturing industries, such as the inspection process, calibration of industrial measurement instruments, testing, traceability, and process monitoring. Among the IR4.0 technologies, three major contributors to digitalising several metrological practices, including the Industrial Internet of Things (IIoT), Big data analytics, and artificial intelligence. Technologies such as cyber security, autonomous systems, and additive manufacturing are essential to ensure M4.0 adoption, thus necessitating future studies on their contribution to the adoption process. It is paramount for developing countries to set a systematic roadmap or framework that considers a holistic paradigm shift to a new metrology approach than adopting solution-based metrological practices.
... Gökalp, Şener and Eren (2017) compared seven maturity models for I4.0 assessment, namely Rockwellautomation, Geissbauer, Vedso and Schrauf (2016), Schumacher et al. (2016), Lanza, Nyhuis, Ansari, Kuprat and Liebrecht (2016), Menon, Kärkkäinen & Lasrado (2016), Leyh, Schäffer, Bley and Forstenhäusler (2016). Bertolini et al. (2019) developed a qualitative review of the models applied in I4.0, for six dimensions (dimensions, key indicators, maturity measurement, calculation tool, presentation of results and maturity stages) and proposing future perspectives to improve existing models and develop new ones. ...
Purpose: This research investigates Portuguese manufacturing companies' Industry 4.0 (I4.0) maturity perception level and proposes an index to measure that aim.Design/methodology/approach: This study uses a survey method to gather the companies' perceptions of their I4.0 maturity level and applies subsequent exploratory factor analysis to propose a global I4.0 measurement index.Findings: The research results show that the most critical factors in evaluating the perception level of I4.0 Perception Maturity (IPM) are strategy, leadership, and customer experiences. The result for the Global Index was 53.50%. Hence, the global Index companies' perception of the level of maturity of I4.0 in Portugal is medium.Research limitations/implications: This study encompasses only Portuguese manufacturing organizations (50 valid responses). Moreover, the research is subject to the limitations of the survey methodology, such as possible respondent bias.Practical implications: The Portuguese I4.0 strategy mainly targets small and medium-sized enterprises through a bottom-up approach. Hence, companies need proper methodologies and tools for evaluating I4.0 adoption, identifying their present situation concerning I4.0 and where to focus on improving the process and achieving the intended benefits.Social implications: This research identifies the main perceived benefits and obstacles of adopting I4.0, suggesting avenues for its successful implementation by the Portuguese companies.Originality/value: This study provides a valuable tool for manufacturing companies to identify the factors that need to be improved to create significant growth in the I4.0 Perception Maturity (IPM) index. Therefore, it can support companies in establishing a roadmap for successful I4.0 adoption and improving their performance and competitive position accordingly.
... These models offer comprehensive guidance that supports an improvement in certain tasks-in this case, the implementation of Industry 4.0. These usually include qualitative dimensions and levels of progress that allow assessing the company through a set of guiding questions [11,12,14,22,23]. • A roadmap is a comprehensive plan that includes dimensions and drivers for digital transformation in an organized approach. ...
Nowadays, different Industry 4.0 technologies have been implemented into diverse industries. However, these implementations are not standardized across similar industries and countries. Consequently, companies are actively looking for assessment instruments—maturity models, roadmaps, frameworks, readiness assessments—to assist in their digital transformation, to determine their Industry 4.0 level, and to identify technologies and strategies that should be implemented in specific areas, thus developing a feasible implementation plan. A review is conducted following the PRISMA (Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses) methodology to analyze the different research works on assessment instruments focused on Industry 4.0. A total of 538 articles, book chapters, conference proceedings, editorial material, reviews, and reports written in the English language were retrieved. Of these, 132 research papers were examined using a mixed analysis format to generate bibliometrics, and 36 articles were then deeply studied for a complete meta-analysis. The findings and insights of this meta-analysis led to a compilation and summary of dimensions, outcomes, enablers, and key components typically involved in Industry 4.0, which are comprehensively integrated to present the best practices for assessing Industry 4.0 and deploying a digital transformation that can impact productivity, flexibility, sustainability, quality, costs, and time.
... As previously mentioned, Industry 4.0 MMs have similar and different scopes, the similar scopes classify I4.0 environment: (1) organizational strategy, which address the strategic planning and control of I4.0 business strategy in terms of IT investments, implementing I4.0 roadmap, cyber security, realizing available resources for digitization, HI & VI [3,5,7,8,15,18]. (2) smart factory, which aims to establish a highly automated productive environment (e.g., Equipment infrastructure, IT systems like ERP, MES, Digitized machines, Traceability (final products, raw materials), Energy Management (Energy consumption, Energy monitoring), Automation (automated identification, industrial robots, M2M communication), Virtualization (AI for maintenance, AI for production), Flexibilization (Flexible line, additive manufacturing) [7][8][9]. ...
... (4) smart products, which aims to facilitate the automated and efficient production management (e.g., using ICT functions of product for self-reporting, identification, localization, Online presence, Integrated customer management, Customized products, and Data processing [1,3,[7][8][9]12]. (5) Vertical Integration (VI) & Horizontal Integration (HI) which aims to the integration of the different departments inside an enterprise (e.g., procurement, production) and outside enterprise like the SC members (e.g., suppliers, manufacturer, and external customers) [9,[18][19][20][21] . (6) Employees, which helps to realize digital transformation of employees through employee's awareness, technical skills, and trainings (e.g., Digital skills, ICT competences of employees, Openness of employees to new technology) [3,5,21] . ...
... In terms of stages, four maturity models (MM) mentioned an (outsider/ absence/basic level/ Initial) stage for SMEs (e.g., MM1 [7,8], MM3 [5], MM5 [3], MM7 [7,13] ). In addition to, MM that studied large enterprises (e.g., MM4 [11], MM10 [6], MM12 [17] , MM14 [18], MM16 [1]). This demonstrates the importance of the basic stage specifically for the newcomers SMEs that have never utilized any I4.0 projects and are willing to pave a vision of adoption [1]. ...
The purpose of this study is to conduct a theoretical review of the existing Industry 4.0 (I4.0) Maturity Models (MM) in the manufacturing sector, with a focus on both large and small and medium enterprises (SMEs), to gain an in-depth understanding of the present state-of-the-art A comprehensive analysis was conducted on a total of sixteen maturity models within the manufacturing sector, encompassing a range of scopes and stages. Notably, only six of these studies specifically focused on SMEs. In order to achieve this objective, the present study has identified the common scopes of MM (manufacturing sector) that have been examined in the context of both large/multinational enterprises and SMEs. These scopes include organizational strategy, smart factory, smart operation, smart product, vertical integration (VI), horizontal integration (HI), employees, leadership, customers, culture, governance, technology, data-driven governance, IT infrastructure, and information systems. In the context of MM stages, research emphasized on an initial/basic stage level that enables SMEs to facilitate the adoption of I4.0 in the manufacturing sector.
... In the literature, there are a limited number of previous studies that review maturity models in different contexts [20][21][22][23][24][25][26][27][28]. These studies are grouped into two: (1) review is the main goal (systematic or regular review papers), and (2) review is only a part of the study (as a related work) which aims to develop a model. ...
... Mittal et al. [23] evaluated 15 different maturity models of the Industry 4.0 [20,22,24,25,[29][30][31][32][33][34][35][36][37] from the perspective of a manufacturing SME. Their comparison is based on SME requirements in terms of finance, technical resource availability, standards, organization culture, employee participation, alliances, and collaboration. ...
... Gokalp et al. [22] mentioned seven maturity models (including one in German) [29,31,35,37,40,41]. Models are compared based on the criteria defined in [42] in terms of fitness for purpose, completeness of aspects, the granularity of dimensions, definition of measurement attributes, description of assessment method, and the objectivity of the assessment method. ...
Industry 4.0 changes traditional manufacturing relationships from isolated optimized cells to fully integrated data and product flows across borders with its technological pillars. However, the transition to Industry 4.0 is not a straightforward journey in which organizations need assistance. A well‐known approach that can be utilized during the early phases of the transition is to assess the capability of the organization. Maturity models are frequently used to improve capability. In this systematic literature review (SLR), we analyzed 22 maturity and readiness models based on 10 criteria: year, type, focus, structure, research methodology followed during the design of models, base frameworks, tool support, community support, objectivity, and extent of usage in practice. Our SLR provides a well‐defined comparison for organizations to choose and apply available models. This SLR showed that (1) there is no widely accepted maturity/readiness model for Industry 4.0, as well as no international standard; (2) only a few models have received positive feedback from the industry, whereas most do not provide any practical usage information; and (3) the objectivity of the assessment method is controversial in most of the models. We have also identified a number of issues as open research areas for assessing readiness and maturity models for Industry 4.0.
... To overcome this dilemma, Mittal et al. [74] suggest the installation of a strategy department or a dedicated Industry 4.0 group for SMEs that can work with the input provided by the maturity model. Stepwise/incremental transformation subsequently leads to success [36,85]. However, the "interdimensional interrelationship" of the dimensions must be considered [41] and managed using an iterative review of the maturity level [80,86]. ...
... Strategy and Leadership [17,[35][36][37][38][39][40][41][42][43][44][45][46][47][48] Customer and Product [36,[49][50][51][52][53][54][55] Operations/Processes [10,11,36,39,44,53,[55][56][57][58][59][60][61] Culture/Organization [35,42,[61][62][63][64][65][66][67][68] People/Qualification [42,44,60,61,[69][70][71][72] Governance [47,49,70,73] Technology [11,30,39,42,44,46,54,56,58,67,[74][75][76][77][78] Investments [39,41,44,46,53,69,79,80] Network, Supply Chain, Data [9,12,20,42,53,61,65,67,69,70,75,77,[81][82][83][84] Project Management [36][37][38][39]41,42,45,48,51,53,57,59,67,74,80,85,86] ...
Background: Industry 4.0 signifies a profound global transformation in production and service activities through its novel organizational principles, including digital connectivity, information transparency, technical assistance, and decentralized decision making. This transformation poses significant challenges for businesses, particularly small- and medium-sized enterprises (SMEs). In response, maturity models have been developed and adapted to facilitate a transparent and supportive entry into this transformative domain. Method/Aim: This study is dedicated to the comprehensive analysis of Industry 4.0 maturity models through a systematic literature review to identify and evaluate previously published recommendations for the adoption and utilization of Industry 4.0. The aim is to provide valuable insights in this context, with a particular focus on easing entry into this domain for SMEs. Results: Quantitative findings reveal a growing demand for fundamental support when entering this domain, with maturity models capable of meeting the demand for structured guidance. However, these models are currently under-validated, lacking transparency, and are often unsuitable for SMEs. Qualitative results categorize numerous insights and recommendations into ten distinct categories related to Industry 4.0. Conclusions: This paper provides a structured summary to support newcomers, research institutions, and businesses in effectively initiating and optimizing their Industrsy 4.0 activities.
... Применение цифровых технологий в производственной среде, в том числе на промышленных предприятиях строительной индустрии (далее -ППСИ), открывает новую эру, за которой уже закрепилось название Четвертая промышленная революция, или Индустрия 4.0. Цифровая трансформация привлекает предприятия благодаря различным конкурентным преимуществам, которые она дает [Gökalp et al., 2017]. Например, MacKinsey 1 дает следующую оценку перспективам развития предприятий за счет внедрения цифровой экономики: ...
... ОБЗОР ЛИТЕРАТУРЫ / LITERATURE REVIEW В широком понимании, термин «зрелость» используется для определения, оценки и формирования ориентира и основы для оценки прогресса (например, процесса или технологии) в бизнесе [Gökalp et al., 2017]. Соответственно, «созревающие» объекты или системы с течением времени увеличивают свои возможности в отношении достижения некоторого желаемого будущего состояния. ...
The construction industry is on the verge of large–scale changes as Industry 4.0 is preparing industrial enterprises for serious challenges. Digital transformation can bring significant changes in all areas of enterprise activity. Maturity models are usually used to assess the current situation and measure the digital maturity of an organization. The authors’ four-stage model of digital maturity assessment for construction industry companies has been proposed. When developing the model, it had been decided to move away from general assessments and use specific changes that would occur at construction industry companies in the process of digital transformation as an assessment tool. The model contains fifteen assessment factors, changes of which at various stages are indicators of digital maturity. The proposed model contains a detailed description of the four stages of digital maturity, therefore it can serve not only to assess the digital maturity of industrial enterprises in the construction industry, but can also be used to indicate the goals planned to be achieved in the future as part of digital transformation, in strategies or business models of enterprises. A distinctive feature of the model is evaluation factors reflecting the degree of integration of the digital environment of industrial enterprises with BIM models of construction organizations.
... One of the methods used to improve organisational performance is maturity models, which help organisations achieve the expected skills in specific dimensions with the use of a continuous improvement approach (Jesus, 2020). A study (Gökalp et al., 2017) reviewed the literature and found seven relevant industry 4.0 maturity models, which were then subjected to an assessment test. The results showed that none of the maturity models satisfied all the criteria and that they need to be further improved. ...
Today, EU projects represent a significant factor in growth and progress of the Croatian economy. Since Croatia joined the European Union, it has utilised a significant amount of HRK for research and development projects. Research and development projects have a long lead time—over four years on average—from the beginning of the idea to the end of implementation. Several stakeholders are involved in the process, including institutions, academia, SMEs, and consulting firms. The level of readiness of the process for digitalisation varies depending on the project lifecycle phase. Since digitalisation is widely recognized as the key to success in service businesses, this study aims to establish a digitalisation heatmap for administrative and operational processes in the EU-funded research and development project lifecycle and recognize opportunities for digitalisation of the process. Data were collected through an empirical study of EU-funded project. Taken together, these findings suggest that there is a potential for further digitisation of the process, especially for consultants in the implementation phase and communication with the client as well as in state institutions. Further research should focus on identified subprocesses to successfully develop a methodology to increase digitisation readiness and on extraordinary circumstances that result in changes of lesser or greater significance to the project.
... One of the methods used to improve organisational performance is maturity models, which help organisations achieve the expected skills in specific dimensions with the use of a continuous improvement approach (Jesus, 2020). A study (Gökalp et al., 2017) reviewed the literature and found seven relevant industry 4.0 maturity models, which were then subjected to an assessment test. The results showed that none of the maturity models satisfied all the criteria and that they need to be further improved. ...
Today, EU projects represent a significant factor in growth and progress of the Croatian economy. Since Croatia joined the European Union, it has utilised a significant amount of HRK for research and development projects. Research and development projects have a long lead time—over four years on average—from the beginning of the idea to the end of implementation. Several stakeholders are involved in the process, including institutions, academia, SMEs, and consulting firms. The level of readiness of the process for digitalisation varies depending on the project lifecycle phase. Since digitalisation is widely recognized as the key to success in service businesses, this study aims to establish a digitalisation heatmap for administrative and operational processes in the EU-funded research and development project lifecycle and recognize opportunities for digitalisation of the process. Data were collected through an empirical study of EU-funded project. Taken together, these findings suggest that there is a potential for further digitisation of the process, especially for consultants in the implementation phase and communication with the client as well as in state institutions. Further research should focus on identified subprocesses to successfully develop a methodology to increase digitisation readiness and on extraordinary circumstances that result in changes of lesser or greater significance to the project.
